Core automated monitoring system

ABSTRACT

An automated monitoring system and method of operation is provided for a nuclear reactor having a pressure vessel containing a reactor core for boiling water to generate steam. A plurality of monitors provide signals for respective monitoring parameters for monitoring operation of the reactor, and a computer includes a data base therein containing predetermined setpoints for the monitoring parameters. The computer identifies abnormal and normal behavior of the monitoring parameters based on the data base, and determines the cause of abnormal behavior of the monitoring parameters using artificial intelligence. A warning is also provided to identify the cause of the monitoring parameter abnormal behavior. And, automatic mitigation action may also be effected.

This is a continuation of application Ser. No. 07/909,343, filed Jul. 6,1992, now U.S. Pat. No. 5,309,485.

The present invention relates generally to nuclear reactors, and, morespecifically, to a system for monitoring performance of the reactor corefor determining the cause of abnormal behavior.

BACKGROUND OF THE INVENTION

A conventional boiling water reactor (BWR) includes a pressure vesselcontaining a reactor core for boiling water to generate steam forpowering a steam turbine-generator for generating electrical power, forexample. The BWR includes several conventional closed-loop controlsystems which control various individual operations of the BWR inresponse to demands.

For example, a conventional recirculation flow control system (RFCS) isused to control core flowrate, which in turn controls output power ofthe reactor core. A conventional control rod drive system, i.e. rodcontrol system (RCS), controls the control rod position and therebycontrol rod density within the reactor core for controlling reactivitytherein. A conventional feedwater control system controls the feedwatersupplied to the pressure vessel, including its flowrate, and thereby thewater level within the pressure vessel, and the feedwater temperature isalso controlled. And a conventional turbine control controls steam flowfrom the BWR to the turbine based on lead demands and pressureregulation. All of these systems as well as other conventional systemsutilize various monitoring parameters of the BWR for controllingoperation thereof. Exemplary conventional monitoring parameters includecore flow or flowrate effected by the RFCS, core pressure which is thepressure of the steam discharged from the pressure vessel to theturbine, neutron flux, feedwater temperature and flowrate, steam flow orflowrate provided to the turbine, core power, and various statusindications of the BWR systems. Many of the monitoring parametersinclude conventional monitors or sensors for directly measuring themonitored parameter, whereas other monitoring parameters such as corepower are conventionally calculated using other monitoring parameters,and the status monitoring parameters are provided as output signals fromthe respective systems.

Conventional control parameters which include several of the monitoringparameters listed above are conventionally used for controllingoperation of the BWR. The control parameters include, for example, coreflow which controls reactor output power, control rod position whichcontrols reactivity in the core, and feedwater flow and temperaturewhich control water level within the pressure vessel and subcooling ofthe water contained therein, respectively. The several control systemsconventionally control operation of the reactor in response to givendemand signals such as load demand. A computer program is conventionallyused to analyze thermal and hydraulic characteristics of the reactorcore for the control thereof, The analysis is based on nuclear dataselected from analytical and empirical transient and accident events,and from conventional reactor physics and thermal-hydraulic principles.For example, core response to core flow changes in a BWR is related toconventionally known temperature, Doppler, Void, and power coefficientsof reactivity, which reflect the conventional reactor physics andthermalhydraulic principles.

However, in the event of an abnormal transient event the operator onduty in the control room is required to manually react to the event atthe very moment of the event based on his training, experience, andjudgment. The remedial action taken may or may not be correct dependingon the training and knowledge of the operator, and, in the latter event,an unnecessary reactor scram may be required. Furthermore, sometransient events may occur exceptionally fast, and faster than thecapability of a human operator to react thereto. In such an event, areactor scram may be automatically effected.

One of the conventional reactor control systems is the nuclear systemprotection system (NSPS) which is a multi-channel electrical alarm andactuating system which monitors operation of the reactor, and uponsensing an abnormal event initiates action to prevent an unsafe orpotentially unsafe condition. The NSPS conventionally provides threefunctions: (1) reactor trip which shuts down the reactor when certainmonitored parameter limits are exceeded; (2) nuclear system isolationwhich isolates the reactor vessel and all connections penetrating thecontainment barrier; and (3) engineered safety feature actuation whichactuates conventional emergency systems such as cooling systems andresidual heat removal systems, for example.

Unless the operator promptly and properly identifies the cause of anabnormal transient event in the operation of the reactor, and promptlyeffects remedial or mitigating action, the nuclear system protectionsystem will automatically effect reactor trip, which is undesirable ifnot required.

OBJECTS OF THE INVENTION

Accordingly, one object of the present invention is to provide a new andimproved monitoring system for a nuclear reactor.

Another object of the present invention is to provide a reactormonitoring system which automatically determines possible causes of anabnormal reactor condition.

Another object of the present invention is to provide an automatedreactor monitoring system using artificial intelligence to identify thecause of reactor abnormal operation and provide a diagnosis message tothe reactor operator.

Another object of the present invention is to provide an automatedreactor monitoring system which is independent of the nuclear systemprotection system and is effective for mitigating the reactor abnormalcondition.

SUMMARY OF THE INVENTION

An automated monitoring system and method of operation is provided for anuclear reactor having a pressure vessel containing a reactor core forboiling water to generate steam. A plurality of monitors provide signalsfor respective monitoring parameters for monitoring operation of thereactor, and a computer includes a data base therein containingpredetermined setpoints for the monitoring parameters. The computer alsoincludes means for identifying abnormal and normal behavior of themonitoring parameters based on the data base, and means for determiningthe cause of abnormal behavior of the monitoring parameters usingartificial intelligence. Warning means are also provided to identify thecause of the monitoring parameter abnormal behavior. And, automaticmitigation action may also be effected.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention, in accordance with preferred and exemplary embodiments,together with further objects and advantages thereof, is moreparticularly described in the following detailed description taken inconjunction with the accompanying drawings in which:

FIG. 1 is a schematic representation of a core automated monitoringsystem (CAMSYS) for a nuclear reactor in accordance with one embodimentof the present invention.

FIG. 2 is a graph plotting exemplary monitoring parameters, based onpercent of rated value versus time, for the reactor illustrated in FIG.1.

FIG. 3 is a flow chart representation of the CAMSYS used in combinationwith the reactor 10 illustrated in FIG. 1.

FIG. 4 is a flow chart of the basic logic processing within the CAMSYSillustrated FIGS. 1 and 3.

FIG. 5 is a flow chart representing exemplary artificial intelligencerules based on the knowledge base illustrated in FIG. 4.

FIG. 6 is a flow chart representation for determining the degree oftransient rate of the abnormal monitoring parameter being identified inFIG. 4.

DESCRIPTION OF THE PREFERRED EMBODIMENT(S)

Illustrated schematically in FIG. 1 is an exemplary nuclear reactor 10including a reactor pressure vessel 12 containing a nuclear reactor core14 which in this exemplary embodiment is effective for boiling water 16to generate steam 18. The boiling water reactor (BWR) 10 is used in thisexemplary embodiment for providing the steam 18 to a conventional steamturbine 20 which rotates a conventional electrical generator 22 forproviding electrical power to a conventional electrical utility grid.

In accordance with the present invention, a core automated monitoringsystem (CAMSYS) indicated generally at 24 is provided in conjunctionwith the reactor 10 for automatically monitoring the operation thereofto identify normal and abnormal operation and predict or identify thecause of abnormal transient events, and then provide a diagnosis thereoffor evaluation by a human operator so that the operator may takecorrective mitigative action, or such action may be taken automaticallyby the CAMSYS 24.

The CAMSYS 24 further includes a plurality of conventional sensors ormonitors indicated collectively by the numeral 26 which provide inputsignals thereto. The monitors 26 are conventionally operatively joinedto the reactor 10 and its various control systems for monitoringoperation of the reactor 10 including its core 14, with each monitor 26providing a corresponding electrical signal for a respective monitoringparameter designated MP. Exemplary monitoring parameters MP include:

neutron flux MP₁ provided by a conventional neutron flux monitor 26a inthe reactor core 14 and operatively joined to the CAMSYS 24;

core flowrate MP₂ provided by a conventional core flowrate monitor 26bfound in a conventional recirculation flow control system (RFCS) 28;

control rod density MP₃ provided by conventional position monitors 26c,conventionally found in a conventional red control system (RCS) 30;

feedwater temperature MP₄ and flowrate MP₅ provided by conventionaltemperature and flowrate monitors, both monitors indicated schematicallyby the single box labeled 26d, in a conventional feedwater system 32which separately controls feedwater flowrate and temperature; and

reactor pressure MP₆ provided by a conventional pressure sensor 26e in aconventional pressure regulated turbine control system 34 operativelyjoined to the pressure vessel 12.

Additional, exemplary, conventional monitoring parameters include corethermal power, steam flow, reactor vessel water level, status of theseveral control systems such as the RFCS 28, the RCS system 30, thefeedwater system 32, and the turbine control system 34.

These exemplary monitors, indicated generally by the numeral 26, areconventionally operatively joined through electrical lines to theirrespective control systems which conventionally receive suitable demandsignals 38 from the plant control room. More specifically, the RFCS 28is conventionally used in a boiling water reactor to control outputpower therefrom. The RFCS 28 includes a conventional recirculation pump40 operatively joined to the pressure vessel 12 for receiving a portionof the water 16 therein, which water 16 is pumped to a conventionalcontrol valve 42 and back into the pressure vessel 12 for providingforced recirculation flow therein as is conventionally known. Aconventional positioner or actuator 44 controls the position of thevalve 42, and therefore the flowrate therethrough, in response to aconventional flow controller 46 operatively joined thereto. Aconventional summer 48 receives a flow demand signal 38a and subtractsthe monitored core flowrate signal MP₂ (26b) in a conventional closed,feedback loop for automatically maintaining the desired value of coreflowrate MP₂ (26b). A conventional load demand error signal 52 isprovided by the turbine control 34 to a load, or master, controller 36,which conventionally provides an output signal 36a to anotherconventional summer 54 for combination with the neutron flux signal fromthe monitor 26a provided by a conventional flux controller 56 togenerate the required flow demand signal 38a. The conventional turbinecontrol system 34 also includes a conventional control valve 58operatively joined between the pressure vessel 12 and the steam turbine20 for conventionally controlling the flow of the steam 18 therethrough,and also includes a conventional speed monitor 26f for providing anadditional speed feedback signal to a conventional pressure regulatedturbine controller 60. The turbine controller 60 has conventional inputsignals such as a pressure demand signal 38b conventionally providedthereto.

The RCS system 30 further includes a plurality of conventional controlrod drives 64, represented schematically by the single control rod drive64 illustrated in FIG. 1, which conventionally insert and withdrawconventional control rods 66 into and out of the reactor core 14. Aconventional rod controller 68 is operatively joined to the drive 64 andthe control rod density monitor 26c, which monitors position of thecontrol rods 66 within the reactor core 14 and, therefore, thecollective density thereof. The rod controller 68 conventionallyreceives rod position demand signals 38c for controlling the density ofthe control rods 66 within the reactor core 14.

And, lastly in the exemplary embodiment illustrated in FIG. 1, thefeedwater system 32 includes a conventional feedwater pump 70operatively joined between the condenser of the turbine 20 and thepressure vessel 12 for pumping the condensate from the turbine 20 asfeedwater into the pressure vessel 12. A conventional feedwater flowcontroller 72 is conventionally joined in a closed feedback loop incommunication with the feedwater pump 70 and the feedwater monitor 26dwhich provides an indication of the feedwater flowrate MP₅ to thecontroller 72, with the controller 72 also conventionally receiving asignal for the water level within the pressure vessel 12. A feedwaterflowrate demand signal 38d is conventionally provided to the controller72.

The structures and functions of the control systems 28, 30, 32, and 34are conventional for conventionally controlling operation of the reactor10. Of course, additional conventional systems also exist and operatesimilarly to those already described in conventional closed loopoperation.

In the event of an abnormal operation or condition of the reactor 10,the plant operator is required to analyze the condition and determinewhat mitigating action is required, which is manually effected by theoperator from the control room. For example, a severe abnormal eventsuch as a loss of coolant accident (LOCA) typically requires shut downof the reactor 10 known as a reactor trip or scram. In order toautomatically monitor operation of the reactor 10 and provide automaticreactor trip, a conventional nuclear system protection system (NSPS) 74is provided. The NSPS 74 is an independent system which conventionallyreceives signals from selected ones of the several monitors 26 and, uponsensing an abnormal condition, initiates action to prevent an unsafe orpotentially unsafe condition. The NSPS 74 may effect a reactor trip andshut down the reactor 10 when certain limits of the monitoringparameters MP are exceeded. The NSPS 74 may also effect isolation of thepressure vessel 12 and all connections of the primary pressure boundarythat penetrate the containment barrier. And, the NSPS 74 may actuateconventional engineered safety feature systems such as core cooling andresidual heat removal for protecting the reactor 10. However, the NSPS74 is able only to monitor operation of the reactor 10 and initiatethese predetermined actions upon sensing the required abnormalconditions. The NSPS 74 is not able to determine the cause of theabnormal condition, which cause must be conventionally determined by theoperator based on the experience and knowledge of the operator toevaluate any abnormal conditions observed. The NSPS 74 is also not ableto provide any mitigation measures to prevent a reactor trip fromoccurring.

For example, illustrated in FIG. 2 is a graph plotting time in secondson the abscissa and percent of rated value on the ordinate. Shown insolid line designated 76 is a core flowrate (MP₂) curve provided by themonitor 26b; shown in dashed line 78 is a neutron flux (MP₁) curveprovided by the monitor 26a; shown in dash-dot line 80 is a feedwaterflowrate (MP₅) curve provided by the monitor 26d; and shown indash-double dot line 82 is steam flowrate from the vessel 12 to theturbine 20 provided by a conventional monitor (not shown). At time zeroin the graph, an abnormal transient event begins which causes acorresponding change in the several monitoring parameters illustrated inFIG. 2 as well as in other conventional monitoring parameters not shownin this example. Confronted with the changing curves illustrated in FIG.2, including the many more not shown therein, an operator would attemptto determine the cause of the abnormality based on the experience andknowledge of the operator, and then attempt to mitigate the problem.Since various types of abnormalities may occur in the operation of therelatively complex reactor 10, detecting the abnormality and thenattempting to mitigate the abnormality within a time period compatiblewith human reaction capability may be relatively easy to relativelydifficult depending on the abnormality and the operator's ability.

In accordance with the present invention, the CAMSYS 24 is provided forautomatically identifying abnormal and normal behavior of the monitoringparameters MP; automatically determining the cause of the abnormalbehavior of the monitoring parameters MP; and then at least providing awarning to the operator in the control room which identifies the likelycause.

The overall relationship of the CAMSYS 24 to plant operation isillustrated in FIG. 3. When normal plant operation is disturbed by anexternal disturbance, such as an operator error or a componentmalfunction, the ,plant then enters an abnormal status. The disturbancemay effect a minor transient condition in the reactor which may bestabilized or corrected by the conventional control systems as wouldtypically occur during normal operation of the plant. The disturbancemay effect a severe transient or accident event which will activate theNSPS 74 to effect reactor scram. Accordingly, a primary function of theCAMSYS 24 is to automatically detect the abnormal status early in thetransient event and provide a warning to the plant operator through aconventional monitor 84, for example located in the plant control room.The warning will preferably indicate the likely cause of the abnormalevent which preferably can also be automatically mitigated by the CAMSYS24 for reducing the consequences resulting from the abnormal condition.The monitoring and mitigation control functions of the CAMSYS 24 arepreferably totally independent from the NSPS 74 so that the safetyoperation of the NSPS 74 is not affected by the CAMSYS 24 and willoperate as intended. Safe plant scram operation is always available ifthe severe transient or accident event cannot be mitigated eithermanually by the plant operator or automatically by she CAMSYS 24.

The CAMSYS 24 illustrated in FIG. 1 preferably includes a CAMSYScomputer 24a which may be a conventional programmable microprocessorconventionally containing the required data base stored in memory, andmonitoring and control software algorithms in accordance with thepresent invention. The signals from the monitors 26 are provideddirectly therefrom to the CAMSYS computer 24a in parallel with theseveral control systems 28, 30, 32, 34 and the NSPS 74 as shown by thebroken lines indicating the electrical connections therebetween.

The basic logic processing flow chart for the CAMSYS 24 is illustratedin FIG. 4 which receives the input signals of the several monitoringparameters MPs from the respective monitors 26, such as the exemplarysignals represented by the curves of FIG. 2. Since many of themonitoring parameters are interrelated by conventional reactor physicsand thermal hydraulic principles, a single abnormal event will effecttransient operation in many of the monitoring parameters. Accordingly,the CAMSYS 24 is a knowledge based system containing predeterminedartificial intelligence rules selected for identifying abnormal andnormal behavior of the monitoring parameters, and from the abnormalmonitoring parameter, determining the cause of the abnormal behavior.

For example, an operator examining the monitoring parameter curvesillustrated in FIG. 2 would use learned experience and knowledge in anattempt to analyze the behavior and predict the cause thereof. In FIG.2, an abnormal condition occurs at time zero with all of the exemplarymonitoring parameters increasing at various rates. Of course, in normaltransient events such as those following a conventional demand for powerincrease, the monitoring parameters also increase, or decrease as thecase may be, based on normal behavior thereof which adds to thedifficulty in predicting abnormal over normal behavior. In FIG. 2, anunidentified abnormal cause leads to a rapid increase in neutron flux(MP₁) as shown by the curve 78, which upon reaching a predeterminedsetpoint of about 120% of rated value effects a protective reactor tripor scram by the NSPS 74 for shutting down the reactor 10, which occursat about 7 seconds. Shortly thereafter the steam flowrate decreases toabout 0% as shown by curve 82, and the core flowrate MP₂ and feedwaterflowrate MP₅ as represented by the curves 76 and 80 behave in a normalfashion following a reactor trip.

The conventional NSPS 74 conventionally monitors and protects operationof the reactor 10 using the several monitors 26 and conventionallysenses abnormal behavior thereof which may include a particularmonitoring parameter exceeding a predetermined magnitude limit orsetpoint or a predetermined rate of change of that magnitude asrepresented by a corresponding limit or setpoint. Depending upon theseverity of the abnormal behavior, the NSPS 74 effects reactor scram,isolation, and/or the safety systems. However, the NSPS 74 does notinclude the capability to identify the cause of the abnormal behavior orprevent reactor trip.

Accordingly, the CAMSYS 24 illustrated in FIG. 4 preferably includes aconventional data base 86 containing predetermined setpoint or limitvalues for the monitoring parameters MPs such as those used in the NSPS74, which include magnitude and rate of change setpoints fordifferentiating between normal and abnormal behavior of the severalmonitoring parameters MPs being monitored. The setpoints in the database 86 are more stringent than those in the NSPS 74 to allow forearlier action. The CAMSYS 24 further includes conventional means 88 foridentifying abnormal and normal behavior of the monitoring parametersbased on the data base 86. Analyzing the monitoring parameters MP andcomparing them to predetermined data bases containing magnitude and rateof change setpoints is conventional in the preferred embodiment, theGeneral Electric Transient Monitor (GETRAM) disclosed in U.S. Pat. No4,678,622--W. S. Rowe et al, incorporated herein by reference, may beused for identifying abnormal transient rates of change such as theexcessive increase in neutron flux MP₁ shown in the curve 78 of FIG. 2immediately following the initiation of the abnormal event. In theexample illustrated in FIG. 2, the identifying means 88 shown in FIG. 4uses the predetermined setpoints contained in the data base 86 toexamine each of the monitored parameters MPs to identify and validatethose that affect performance of the reactor core 14 and which indicateabnormal behavior. Each of the monitoring parameters MPs is examined forabnormal behavior. For example, if one of the MPs has an increased ratethat is higher than a certain setpoint rate in the data base 86, thenthis MP indicates an abnormal increase relative to normal plantoperation.

In the FIG. 2 example, the identifying means 88 identify that the coreflowrate MP₂, neutron flux MP₁, feedwater flowrate MP₅, and steamflowrate among others are changing and that the neutron flux MP₁ shownin curve 78 is increasing at an abnormal, excessive rate.

As shown in FIG. 4, the CAMSYS 24 further includes means 90 forautomatically determining the cause of the abnormal behavior of themonitoring parameters MPs without direct human input by the plantoperator, for example. The cause determining means 90 includepredetermined artificial intelligence rules, e.g. software algorithms,associated with each of the monitoring parameters MPs for analyzing anddetermining the cause of the abnormal behavior based on performance ofpreselected ones of the monitoring parameters MPs using the data base 86and a predetermined knowledge base 92.

More specifically, once the abnormally behaving monitoring parametersare identified in the first task by the identifying means 88, theidentified abnormal parameter, or primary monitoring parameter, isfurther analyzed in a second task by the determining means 90 along withthe most closely related monitoring parameters, or secondary monitoringparameters, to determine the characteristics of the transient includingtype of transient and trend of parameter change for identifying thecause of the abnormal behavior. This is accomplished by using thepredetermined knowledge base 92 which is implemented in thepredetermined artificial intelligence rules associated with each of themonitoring parameters.

Since an abnormal condition will typically be reflected in changes ofseveral of the monitoring parameters, it is necessary to evaluate thoserelated parameters to discern abnormal from normal behavior in order toidentify cause. The knowledge base 92, therefore, preferably includes atleast one, and in the preferred embodiment all three, of (1)predetermined analytical transient and accident operating performancesof the reactor 10 which are conventionally obtained; (2) actualoperating records of transient and accident operating performance of thereactor 10 which are also conventionally obtained; and (3) theinterrelationship of the primary and secondary monitoring parametersbased on predetermined reactor physics and thermal hydraulic principleswhich are also conventionally obtained. For example, analytical andempirical data are conventionally known which indicate core performancebased on changes in core flow and control rod density changes, forexample, or based on accidents such as the LOCA. And, core response tocore flow changes is reflected in four interrelated variables, i.e.,core void fraction, Doppler coefficient, core inlet enthalpy change, andxenon concentration change, as is conventionally known. In this way, thesecondary monitoring parameters may be preselected for each primarymonitoring parameter to determine the abnormal behavior cause basedthereon.

One example of the required artificial intelligence rules for the FIG. 2example include the following rules represented schematically in FIG. 5:

(1) If the primary monitoring parameter, e.g. MP₁, such as neutron flux(curve 78) exceeds a predetermined setpoint such as an excessive rateincrease as identified by GETRAM, then check related, secondaryparameters MP₂, MP₃, etc., such as core flowrate (curve 76) and controlrod density change rates (based on the positions of the several controlrods 66).

(2) If the secondary monitoring parameter M P₂, such as core flowrate(curve 76) is changing, or increasing for example, then check status ofits respective control system, e.g. the RFCS 28, to determine whether itis demanding such change or not.

(3) If the secondary monitoring parameter MP₃ is changing, for examplecontrol rod density is changing, then check status of its controlsystem, e.g. RCS system 30 for automatic or manual operation thereof.

(4) Diagnose abnormal problem based on predetermined interrelationshipof the primary monitoring parameter MP₁ and the secondary monitoringparameters MP₂, MP₃, etc., for example, if the core flowrate increasesat an excessive rate, and if there is no demand for such increase, andif there is no control rod density change, then there is a controlproblem in the RFCS 28.

Accordingly, the cause of the abnormal behavior of the exampleillustrated in FIG. 2 is determined to be loss of control of the coreflowrate (curve 76) which is increasing substantially linearly. Forexample, the flow controller 46 illustrated in FIG. 1 may fail, causingthe control valve 42 to abnormally open and increase the core flowratethrough the reactor core 14. As the core flowrate increases (curve 76),the neutron flux increases rapidly (curve 78), and unless mitigatingaction is effected, the NSPS 74 will effect a reactor trip as shown inFIG. 2 at about 7 seconds from initiation of the failure of the flowcontroller 46.

The CAMSYS 24 can, well within the time before reactor trip, identifythe problem, such as the failure of the flow controller 46, and providea warning through the monitor 84 to the plant operator in the controlroom which identifies the cause of the abnormal behavior. For example,the warning displayed by the monitor 84 may simply state "CORE FLOWABNORMAL INCREASE."

The operator may then effect mitigating action, manually withoutautomatic operation from CAMSYS 24, for example, by conventionallyplacing the flow controller 46 in manual, and sending a suitableoverride signal 38e as shown in FIG. 1 to a conventional manual overridecontroller 94 operatively joined to the actuator 44, and byconventionally actuating the RCS 30 (signal 38c) to insert selectedcontrol rods 66.

In this exemplary embodiment, the primary monitoring parameter isneutron flux MP₁ and the secondary monitoring parameters include coreflowrate MP₂ and control rod density change rate MP₃, and may alsoinclude feedwater flowrate MP₅ and reactor pressure MP₆ allconventionally known to be interrelated. And, the artificialintelligence rules identify the recirculation flow control systemproblem as a likely cause of the abnormal behavior of the neutron fluxexceeding a given setpoint wherein the core flowrate also exceeds agiven setpoint without normal demand therefore, and the control roddensity change rate is substantially unchanged.

Of course, this is but one relatively simple example of the artificialintelligence rules contained in the knowledge base 92 of the CAMSYScomputer 24a. As shown in FIG. 5, these rules are but one branch of themany branches which may be created for evaluating each desiredmonitoring parameter MP and interrelated secondary monitoringparameters. The artificial intelligence rules may be as sophisticated asdesirable based on the degree of sophistication to conventionallyanalyze abnormal symptoms in advance and provide suitable artificialintelligence rules for allowing the causes of the abnormal symptoms tobe analyzed and identified with suitable accuracy. The rules may be assimple as the exemplary rules presented above or may be more complexbased upon conventionally known interrelationships of parameter trendsas defined by reactor physics and thermal hydraulic principles as wellas on analytical and empirical data reflecting plant transient andaccident events.

The CAMSYS computer 24a may further include as shown in FIG. 4additional means 96 for determining at least one control parameter CP tocontrol or mitigate the monitoring parameter abnormal behavior eitherdisplayed through the monitor 84 to the operator for manual correction,or for automatic mitigation effected by the CAMSYS 24 itself. Exemplaryconventionally known control parameters CPs include core flowrate andcontrol rod position, which are the primary parameters for controllingoperation of a boiling water reactor, with additional control parametersincluding feedwater flowrate, load demand, and others including severalof the monitoring parameters MPs themselves. There is an overlap betweenthe monitoring parameters MPs and the control parameters CPs which isconventionally known, with some parameters providing both monitoringinformation and control functions. As shown in FIGS. 4 and 5, thecontrol parameter determining means 96 use suitable artificialintelligence rules from the knowledge base 92 and data from the database 86 to determine which control parameters CPs may be used tomitigate the abnormal transient event.

For example, once it is determined that the flow controller 46 hasfailed and, therefore, control over the core flowrate has been lost, thecore flowrate becomes the primary control parameter CP₁ for controllingthe excessive increase in neutron flux. One or more secondary controlparameters may also be selected which also assist in controlling theneutron flux such as control rod position which effects control roddensity CP₂ in the reactor core 14 and therefore neutron flux. Thesecondary control parameters are preselected for each predeterminedabnormal symptom and are contained in the knowledge base 92, again basedupon conventionally known interrelationships of the parameters based onreactor physics and thermal hydraulic principles and analytical andempirical plant transient and accident events. For a predeterminedabnormal symptom, primary and secondary control parameters may bespecified in the knowledge base 92 for use as required when confrontingactual abnormal symptoms.

For the example presented in FIG. 2 and discussed above, the warningmessage displayed in the monitor 84 may identity the failure of the flowcontroller 46 and suggest mitigation control by manually adjusting thecore flowrate CP₁, i.e., by decreasing the flowrate, or by inserting thecontrol rods 66 to increase rod density CP₂, or both, for preventing theneutron flux level from exceeding the setpoint leading to reactor scram.

As described above, the mitigating action on may be taken manually bythe operator from the plant control room, or, the CAMSYS 24 may furtherinclude means 98 for automatically adjusting the primary or secondarycontrol parameters CPs, or both, to mitigate the monitoring parameterabnormal behavior as shown schematically in FIG. 4. The CAMSYS computer24a illustrated in FIG. 1 may simply include additional conventionalcontrol commands, e.g. in a dedicated CAMSYS controller, which willforward suitable mitigating signal or signals, e.g. 100 a-e, to theappropriate control systems, e.g. 28, 30, 32, 34.

Once the cause of the abnormal behavior is identified and a suitablecontrol parameter CP for mitigating the abnormal behavior is determined,the control parameter CP may be automatically adjusted by the means 98to provide a suitable corrective or mitigating signal to mitigate theabnormal behavior. For the example presented above, the flow controller46 shown in FIG. 1 may be bypassed by automatically providing themitigating signal from the CAMSYS computer 24a as an override signal100e, comparable to override signal 38e, directly to the manual overridecontroller 94 to suitably close the abnormally open control valve 42 toreverse the excessive core flowrate and, thereby, reverse the abnormalincrease in neutron flux. At the same time, another mitigating signal100c, comparable to demand signal 38c, may be automatically provided bythe means 98 within the CAMSYS computer 24a to the rod controller 68 tofurther insert selected control rods 66 for also reducing the neutronflux to a more normal level. And, yet another mitigating signal 100d,comparable to demand signal 38d, may be provided to flow controller 72to suitably adjust feedwater flow.

The CAMSYS computer 24a may also provide a mitigating signal 100adirectly to the summer 48 to automatically adjust recirculation flow asrequired during abnormal events when the flow controller 46 isfunctioning properly and does not require override.

As shown in FIG. 4, the schematic feedback control joined to arespective output line 100 which carries the respective mitigatingsignal is any suitable feedback control system of the reactor 10 whichis selected for mitigating the abnormal behavior. The monitor 84 maythen also display the problem diagnosis and the corrective actionautomatically effected. The adjusting means 98 may provide a suitablemitigating signal to the respective feedback control systems of thereactor 10 for conventional closed loop feedback operation. The degreeof control adjustment depends on the severity of the abnormal transient.This can be achieved through conventional logic that responds tosubstantially instantaneous and infinitesimal changes of the MP signal.Preferably, the adjusting means 98 within the CAMSYS computer 24aincludes conventional "fuzzy" logic for mitigating the abnormaltransient event. Fuzzy logic may be useful to improve mitigationperformance where the interrelationship between the several parametersis complex and in view of the prolonged conventional time lags andoscillatory responses between demand changes in the control parametersand the response as observed by the monitoring parameters inconventional continuous control logic.

Since transient abnormal events may vary in rate from relatively slow torelatively fast, the identifying means 88 illustrated in FIG. 4 may beconventionally selected to discern the different rates as illustratedschematically in FIG. 6. The rate of change of the monitoring parameterMP may be conventionally determined, for example by using the GETRAM,which determines the rate of the abnormal behavior including a firstrate A which may be classified as a slow transient, a second rate Bwhich may be classified as a fast transient relative to the slowtransient, and a third rate C which may be classified as a very fast orsevere transient which is in turn faster than the fast transient of rateB. The three rates A, B, and C are preferably predetermined ranges ofrates with the range below the slow transient rate A being defined asstable operation wherein no mitigating action is required or taken andno message is displayed from the monitor 84. If any one monitoringparameter MP is greater than the stable rate of change, it will fallinto one of the three rates A, B, and C which will determine therespective levels L1, L2, and L3 of mitigation required, eitherdisplayed in the monitor 84 to be effected manually by the operator inthe control room or effected automatically by the adjusting means 98. Asshown additionally in FIG. 3, the slow and fast transients may beconsidered minor transients which can be mitigated without reactorscram, whereas the severe transient, including an accident event, willrequire actuation of the NSPS 74 to scram the reactor 10 and isolate thereactor and effect the safety systems as conventionally required.

Accordingly, the adjusting means 98 may include suitable algorithmsindicating the respective levels L1, L2, and L3 of mitigation requiredbased on the severity of the observed abnormal transient. Again withrespect to the core flowrate example presented above, if the increase incore flowrate is relatively slow, the mitigation level L1 may merelyrequire manual control of the actuator 44 by the manual overridecontroller 94 in response to the CAMSYS computer 24a, or the controlrods 66 may be additionally inserted into the core 14 as directed by theCAMSYS computer 24a. For automatic control by the CAMSYS computer 24a inlevel L1, mitigation is effected using relatively small corrections. Ifthe core flowrate abnormality is within the fast transient range, thesecond mitigation level L2 may require at least both of these correctiveactions with medium sized corrections. And, if the core flowrateincrease is within the severe transient range, with the neutron fluxlevel increasing at a severe rate, the third mitigation level L3 iseffected with the largest corrections. The NSPS 74 may possibly effectreactor scram if the mitigation is not effective to ameliorate theabnormal behavior quickly enough, but its independent operation isnevertheless maintained.

For example, the NSPS 74 is actuated when the neutron flux curve 78 ofFIG. 2 reaches a predetermined maximum limit such as the 120%illustrated in FIG. 2. However, the CAMSYS 24 may automatically mitigatethe cause of the neutron flux abnormal increase prior to it reaching the120% limit, thus preventing reactor scram. Since the CAMSYS 24 iscompletely independent of the operation of the NSPS 74, an improved, andnow intelligent, overall system is obtained with the NSPS 74 retainingits ability to effect reactor scram.

Since the CAMSYS 24 is microprocessor based using the computer 24a, allrequired logic therein may be conventionally programmed usingconventional software algorithms. The degree of sophistication andcomplexity of the algorithms may vary from relatively simple torelatively complex based on the experience and knowledge base intendedto be utilized. The CAMSYS 24 preferably includes evaluation of themagnitude and rates of change of the several monitoring parameters MPs.It may also further include second-order changes in the monitoringparameters. Although the exemplary monitoring parameters MPs are thosespecifically associated with performance of the reactor core 14 itself,additional monitoring parameters may be utilized for monitoring otherplant functions indirectly associated with performance of the core 14.Conventional principles of neural networks which may be combined withfuzzy logic technology may be also utilized for more extensivemonitoring and control of plant abnormal operating status.

Although the CAMSYS 24 has been described with respect to a conventionalboiling water reactor (BWR) it may also be used for other types ofreactors such as a pressurized water reactor (PWR). The data base,knowledge base, and algorithms will, of course, be suitably modified tofit the operating principles of the PWR.

The CAMSYS 24 is a flexible system providing the ability to monitorselected monitoring parameters which reflect core performance, forexample, to determine abnormal operation thereof. And, mostsignificantly, the CAMSYS 24 utilizes artificial intelligence rulesbased on performance interrelationships between monitored parametersusing conventional and well known principles including reactor physicsand thermal-hydraulics, and analytical and empirical data representativeof transient and accident events to determine the cause or causes of theabnormal behavior. The predicted cause is provided to the operator forhis evaluation and action as required, or may be automatically mitigatedby the CAMSYS 24 as described above. The CAMSYS 24, therefore, utilizesthe predetermined knowledge base 92 to at least assist the operator inidentifying abnormal transient causes for improving control of thereactor 10.

While there have been described herein what are considered to bepreferred embodiments of the present invention, other modifications ofthe invention shall be apparent to those skilled in the art from theteachings herein, and it is, therefore, desired to be secured in theappended claims all such modifications as fall within the true spiritand scope of the invention.

Accordingly, what is desired to be secured by Letters Patent of theUnited States is the invention as defined and differentiated in thefollowing claims:
 1. A system for receiving monitoring parameter inputsignals from a plurality of monitors monitoring operation of a nuclearreactor said system comprising:a data base containing predeterminedsetpoints; means for identifying abnormal behavior of said nuclearreactor by utilizing said setpoints and said input signals from saidmonitors; means for determining a cause of said identified abnormalbehavior including predetermined artificial intelligence rulesassociated with each primary one of said monitoring parameters and basedon performance of preselected related secondary ones of said monitoringparameters; and means for determining a control parameter to mitigatesaid abnormal behavior.
 2. A system according to claim 1 furthercomprising means for providing a warning identifying said abnormalbehavior cause.
 3. A system according to claim 2 wherein said secondarymonitoring parameters are preselected for each primary monitoringparameter to determine said abnormal behavior cause based on all threeof:predetermined analytical transient and accident operating performanceof said reactor; actual operating records of transient and accidentoperating performance of said reactor; and interrelationship of saidprimary and secondary monitoring parameters based on predeterminedreactor physics and thermal hydraulic principles.
 4. A system accordingto claim 2 wherein said secondary monitoring parameters are preselectedfor each primary monitoring parameter to determine said abnormalbehavior cause based on at least one of:predetermined analyticaltransient and accident operating performance of said reactor; actualoperating records of transient and accident operating performance ofsaid reactor; and interrelationship of said primary and secondarymonitoring parameters based on predetermined reactor physics and thermalhydraulic principles.
 5. A system according to claim 4 wherein saidprimary monitoring parameter is neutron flux and said secondarymonitoring parameters include core flowrate and control rod densitychange rate; andsaid artificial intelligence rules identify arecirculation flow control system problem as a cause of abnormalbehavior of said neutron flux exceeding a given setpoint wherein saidcore flowrate also exceeds a given setpoint without normal demandtherefor and said control rod density change rage is substantially zero.6. A system according to claim 4 further comprising means for adjustingsaid control parameter to mitigate said abnormal behavior.
 7. A systemaccording to claim 5 wherein said behavior identifying means determinerate of said abnormal behavior including a slow transient, a fasttransient relative to said slow transient, and a severe transient fasterthan said fast transient, with said slow, fast, and severe transientseffecting different levels of mitigation.
 8. A system for controllingthe operation of a nuclear reactor in dependence on monitoring parameterinput signals received from a plurality of monitors placed inside thenuclear reactor, comprising:a data base containing at least a scramsetpoint and a pre-scram setpoint for a primary one of said plurality ofmonitoring parameter input signals, said scram setpoint indicatingrelatively more severe abnormal behavior and said pre-scram setpointindicating relatively less severe abnormal behavior of said reactor;means for comparing said primary one of said plurality of monitoringparameter input signals to said scram setpoint; means for triggeringreactor scram in response to said primary one of said plurality ofmonitoring parameter input signals reaching said scram setpoint; meansfor comparing said primary one of said plurality of monitoring parameterinput signals to said pre-scram setpoint; artificial intelligence meansfor diagnosing the cause of said primary one of said plurality ofmonitoring parameter input signals reaching said pre-scram setpoint,said artificial intelligence means comprising means for checking atleast a secondary one of said plurality of monitoring parameter inputsignals for a predetermined relationship to said primary one of saidplurality of monitoring parameter input signals; and means fortriggering mitigation of said relatively less severe abnormal behaviorof said reactor before the occurrence of said relatively more severeabnormal behavior of said reactor in response to the existence of saidpredetermined relationship.
 9. The system as defined in claim 8, whereinsaid mitigation triggering means comprising means for identifying atleast one control parameter to be adjusted and means for adjusting saidat least one control parameter.
 10. The system as defined in claim 9,wherein said means for identifying at least one control parameter to beadjusted comprising fuzzy logic processing means.
 11. The system asdefined in claim 8, wherein said mitigation triggering means selects amitigation action in dependence on the rate at which a transient eventis proceeding.
 12. The system as defined in claim 8, wherein saidprimary one of said plurality of monitoring parameter input signals isneutron flux.
 13. The system as defined in claim 12, wherein saidchecking means checks first and second secondary ones of said pluralityof monitoring parameter input signals for a predetermined relationshipto said primary one of said plurality of monitoring parameter inputsignals, said first secondary one of said plurality of monitoringparameter input signals being core flowrate and said second secondaryone of said plurality of monitoring parameter input signals beingcontrol rod density change rate.
 14. The system as defined in claim 13,wherein said artificial intelligence means comprise means foridentifying a recirculation flow control system malfunction as a causeof the neutron flux exceeding said pre-scram setpoint when the coreflowrate also exceeds a corresponding pre-scram setpoint without normaldemand therefor and the control rod density change rate is substantiallyzero.
 15. The system as defined in claim 8, further comprising means fordisplaying a warning identifying the cause of said primary one of saidplurality of monitoring parameter input signals reaching said pre-scramsetpoint.
 16. The system as defined in claim 8, wherein said artificialintelligence means comprise a knowledge base including at least one ofthe following:(a) predetermined analytical transient and accidentoperating performances of said reactor; (b) actual operating records oftransient and accident operating performances of said reactor; and (c)the interrelationship of said primary and secondary ones of saidplurality of monitoring parameter input signals based on predeterminedreactor physics and thermal hydraulic principles.
 17. A method forcontrolling the operation of a nuclear reactor in dependence onmonitoring parameter input signals received from a plurality of monitorsplaced inside the nuclear reactor, comprising the steps of:storing adata base containing at least a scram setpoint and a pre-scram setpointfor a primary one of said plurality of monitoring parameter inputsignals, said scram setpoint indicating relatively more severe abnormalbehavior and said pre-scram setpoint indicating relatively less severeabnormal behavior of said reactor; comparing said primary one of saidplurality of monitoring parameter input signals to said scram setpoint;triggering reactor scram in response to said primary one of saidplurality of monitoring parameter input signals reaching said scramsetpoint; comparing said primary one of said plurality of monitoringparameter input signals to said pre-scram setpoint; diagnosing the causeof said primary one of said plurality of monitoring parameter inputsignals reaching said pre-scram setpoint using artificial intelligencerules which include at least a rule for checking at least a secondaryone of said plurality of monitoring parameter input signals for apredetermined relationship to said primary one of said plurality ofmonitoring parameter input signals; and triggering mitigation of saidrelatively less severe abnormal behavior of said reactor before theoccurrence of said relatively more severe abnormal behavior of saidreactor in response to the existence of said predetermined relationship.18. The method as defined in claim 17, wherein said step of triggeringmitigation comprises the steps of identifying at least one controlparameter to be adjusted and adjusting said at least one controlparameter.
 19. The method as defined in claim 18, wherein said step ofidentifying at least one control parameter to be adjusted is performedusing fuzzy logic.
 20. The method as defined in claim 17, wherein saidstep of triggering mitigation comprises the step of selecting amitigation action in dependence on the rate at which a transient eventis proceeding.